Caractérisation du rôle de la famille des prokinéticines dans le contrôle de la chorioamniotite et dans les conséquences neurodéveloppementales néonatales.

La chorioamniotite, infection ascendante de la grossesse est une cause majeure de prématurité et de paralysie cérébrale chez les enfants prématurés. Le laboratoire du Pr Sébire (Research Institute of McGill University Health Center, Montréal) a mis au point un modèle de rates gestantes présentant une chorioamniotite induite par du streptocoque du groupe B. Au cours […]

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Caractérisation non destructive des enrobés bitumineux

Les enrobés bitumineux sont majoritairement utilisés pour revêtir les structures de chaussée. La caractérisation de leur comportement thermomécanique est donc essentielle pour comprendre leur fonctionnement sous charge et dimensionner correctement les structures neuves ou qui doivent être réhabilitées. À l’heure actuelle, la majorité des essais qui permettent de caractériser ces matériaux en laboratoire nécessite des […]

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Artificial Intelligenece to study tumor heterogeneity

High throughput multi-omic cancer studies have described the inter-tumor heterogeneity and led to well defined molecular classifications. Nevertheless, these classifications only reflect the most abundant tumor subtype in the examined sample, thus neglecting intra-tumor heterogeneity, a major source of therapeutic resistance. As advanced microdissection techniques to isolate a cell population of interest from heterogeneous clinical […]

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Evolutionary and functional analysis of genes involved in nitrogen-fixing symbiosis as a case of convergence

A major challenge facing farmers is obtaining the nitrogen needed to support plant growth. Inoculation of legume crops with bacteria known as rhizobia, which supply plants with the required nitrogen, is a green alternative to environmentally hazardous nitrogen-fertilizers. The development of highly-efficient rhizobium inoculants is a pre-requisite for sustainable intensification of agriculture. In five clades […]

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Making AI Ready for Safety-Critical Applications

This project is a collaborative endeavor of researchers (6 supervisors, 3 PhD students and one postdoctoral fellow) which will be either members or visitors of the incoming “International Laboratory on Learning Systems” (ILLS) of the CNRS (starting in early 2022) with Université Paris-Saclay, McGill University and École de technologie supérieure (ETS). We will develop rigorous […]

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Open-air fabrication of dynamic cantilever gas sensor

Sensitive gas sensors are urgently needed for the detection of biomarkers for disease prevention and greenhouse gas emissions for environmental monitoring. Dynamic cantilever gas sensors work by oscillating the cantilever to its natural resonance frequency by typical MEMS (micro electromechanical system)-based actuation methods. The adsorption of a target gas on the cantilever increases its mass […]

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AI based technology adoption in circular economics

This project is a cross-disciplinary study of econometrics and machine learning (ML) models applied to the decision making modelling in industry. The problematic arises from the lack of tools supporting the transition to circular economics model and the need to identify the key factors to influence this transition. The project aims to explore the key […]

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Detection of anomalous emotional responses using attention mechanisms for deep machine learning

Computer-based multimodal affect recognition methods fuse multiple informational channels, typically video, audio, and text, to resolve the emotional state of a monitored individual. The proposed research aims to develop multimodal deep learning models to recognize anomalous emotional responses, which correspond to a deviation from the expected affective reaction for a particular context. Since multimodal affect […]

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Analyse de données métabolomiques et lipidomiques de patients avec insuffisance cardiaque

La métabolomique est une science prometteuse pour identifier de nouveaux marqueurs biologiques associés à l’insuffisance cardiaque à fraction d’éjection préservée (HFpEF), afin d’améliorer son diagnostic et son traitement. Notre projet vise l’utilisation de méthodes de bioinformatiques et d’intelligence artificielle pour l’analyse de données métabolomiques et lipidomiques de patients HFpEF, précédemment générées et prétraitées dans nos […]

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Geophysical detection of microplastics in soils

Plastics pollution is a global environmental hazard with a wide range of impacts on wildlife, biodiversity, food webs, ecosystem services and human wellbeing. Of particular concern are microplastics (including nanoplastics) because their small sizes enhance their long-range transport, their uptake by biota and the capacity to sorb and leach contaminants. The proposed project will focus […]

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Architected materials design using quasi-periodic homogenization

Architected materials are those which have a designed microscopic structure or “microstructure”. They of exhibit material properties which are not attainable by conventional materials. One important field of application for these materials is bone biomechanics, in which the search for suitable bone biosubstitutes is of high scientific and clinical importance. For example, architected materials are […]

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Tokamak Dust Studies Collaboration (STOR-M and WEST)

A fusion reactor is a device capable of producing even more power than a fission reactor, with carbon free emissions and no long lived radioactive waste. No fusion reactor exists as of yet, though the tokamak design is a promising candidate. The goal of a modern tokamak is to produce a fourth state of matter, […]

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